Evapotranspiration of an abandoned grassland in the Italian Alps: Modeling the impact of shrub encroachment

This study analyzes the effect of shrub encroachment on actual evapotranspiration (ETa), a still poorly studied phenomenon in the Alps. The effect of shrub encroachment is investigated on an Alpine grassland in Western Italy using both data and a soil hydrological model (Hydrus 1D), which is used to model three different land covers: grassland, shrubland, and a mixture of the two land covers with a novel double vegetation approach recently introduced. Four growing seasons of eddy covariance measurements are used as an approximate reference for the interpretation and consistency of the model outputs. Also, the impact of meteorological inter-annual variability and of different environmental conditions on both modeled and measured evapotranspiration is analyzed. The modeling results show that the model is able to capture the inter-annual variability of ETa. The double vegetation approach suggests that the percentage of total transpiration flux assigned to the shrubland is between 20 and 60 %. Single-vegetation simulations show that shrubs lead to an enhancement of ETa equal to + 27.1 %, +26.0 %, +26.8 %, and + 23.9 % (range 2014–2017) compared to grassland, which could lead to an alteration of the hydrological cycle. Moreover, chambers measurements of shrubs transpiration show a good agreement with the eddy covariance measurement, suggesting that the ecosystem's behavior is already close to a shrubland, which yields an increased ETa if compared to grassland. The evaporative index from the modeled shrubland is higher (range +24–27 %) than the case of a modeled grassland. Finally, ETa and the evaporative fraction (EF) are in the energy-limited regime in most cases. This result was obtained from the analysis of the relationship between ETa (and EF) and either meteorological variables or soil water content including the simulated one in the 0–100 cm horizon. The following analysis, more focused on micrometeorological variables, namely vapor pressure deficit, net radiation, wind speed, air temperature, and ground heat flux, indicates that ETa is mostly affected by the vapor pressure deficit

SiO2nanoparticles modulate the electrical activity of neuroendocrine cells without exerting genomic effects

Engineered silica nanoparticles (NPs) have attracted increasing interest in several applications, and particularly in the field of nanomedicine, thanks to the high biocompatibility of this material. For their optimal and controlled use, the understanding of the mechanisms elicited by their interaction with the biological target is a prerequisite, especially when dealing with cells particularly vulnerable to environmental stimuli like neurons. Here we have combined different electrophysiological approaches (both at the single cell and at the population level) with a genomic screening in order to analyze, in GT1-7 neuroendocrine cells, the impact of SiO2NPs (50\u2009\ub1\u20093\u2009nm in diameter) on electrical activity and gene expression, providing a detailed analysis of the impact of a nanoparticle on neuronal excitability. We find that 20\u2009\ub5g\u2009mL-1NPs induce depolarization of the membrane potential, with a modulation of the firing of action potentials. Recordings of electrical activity with multielectrode arrays provide further evidence that the NPs evoke a temporary increase in firing frequency, without affecting the functional behavior on a time scale of hours. Finally, NPs incubation up to 24\u2009hours does not induce any change in gene expression

The mycorrhizal root-shoot axis elicits Coffea arabica growth under low phosphate conditions

Coffee is one of the most traded commodities world-wide. As with 70% of land plants, coffee is associated with arbuscular mycorrhizal (AM) fungi, but the molecular bases of this interaction are unknown. We studied the mycorrhizal phenotype of two commercially important Coffea arabica cultivars (‘Typica National’ and ‘Catimor Amarillo’), upon Funnelliformis mosseae colonisation grown under phosphorus limitation, using an integrated functional approach based on multi-omics, physiology and biochemistry. The two cultivars revealed a strong biomass increase upon mycorrhization, even at low level of fungal colonisation, improving photosynthetic efficiency and plant nutrition. The more important iconic markers of AM symbiosis were activated: We detected two gene copies of AM-inducible phosphate (Pt4), ammonium (AM2) and nitrate (NPF4.5) transporters, which were identified as belonging to the C. arabica parental species (C. canephora and C. eugenioides) with both copies being upregulated. Transcriptomics data were confirmed by ions and metabolomics analyses, which highlighted an increased amount of glucose, fructose and flavonoid glycosides. In conclusion, both coffee cultivars revealed a high responsiveness to the AM fungus along their root-shoot axis, showing a clear-cut re-organisation of the major metabolic pathways, which involve nutrient acquisition, carbon fixation, and primary and secondary metabolism

A multiscale hybrid model for pro-angiogenic calcium signals in a vascular endothelial cell

Cytosolic calcium machinery is one of the principal signaling mechanisms by which endothelial cells (ECs) respond to external stimuli during several biological processes, including vascular progression in both physiological and pathological conditions. Low concentrations of angiogenic factors (such as VEGF) activate in fact complex pathways involving, among others, second messengers arachidonic acid (AA) and nitric oxide (NO), which in turn control the activity of plasma membrane calcium channels. The subsequent increase in the intracellular level of the ion regulates fundamental biophysical properties of ECs (such as elasticity, intrinsic motility, and chemical strength), enhancing their migratory capacity. Previously, a number of continuous models have represented cytosolic calcium dynamics, while EC migration in angiogenesis has been separately approached with discrete, lattice-based techniques. These two components are here integrated and interfaced to provide a multiscale and hybrid Cellular Potts Model (CPM), where the phenomenology of a motile EC is realistically mediated by its calcium-dependent subcellular events. The model, based on a realistic 3-D cell morphology with a nuclear and a cytosolic region, is set with known biochemical and electrophysiological data. In particular, the resulting simulations are able to reproduce and describe the polarization process, typical of stimulated vascular cells, in various experimental conditions.Moreover, by analyzing the mutual interactions between multilevel biochemical and biomechanical aspects, our study investigates ways to inhibit cell migration: such strategies have in fact the potential to result in pharmacological interventions useful to disrupt malignant vascular progressio

Lattice permutations and Poisson-Dirichlet distribution of cycle lengths

We study random spatial permutations on Z^3 where each jump x -> \pi(x) is penalized by a factor exp(-T ||x-\pi(x)||^2). The system is known to exhibit a phase transition for low enough T where macroscopic cycles appear. We observe that the lengths of such cycles are distributed according to Poisson-Dirichlet. This can be explained heuristically using a stochastic coagulation-fragmentation process for long cycles, which is supported by numerical data.Comment: 18 pages, 14 figure

Protein docking by Rotation-Based Uniform Sampling (RotBUS) with fast computing of intermolecular contact distance and residue desolvation

<p>Abstract</p> <p>Background</p> <p>Protein-protein interactions are fundamental for the majority of cellular processes and their study is of enormous biotechnological and therapeutic interest. In recent years, a variety of computational approaches to the protein-protein docking problem have been reported, with encouraging results. Most of the currently available protein-protein docking algorithms are composed of two clearly defined parts: the sampling of the rotational and translational space of the interacting molecules, and the scoring and clustering of the resulting orientations. Although this kind of strategy has shown some of the most successful results in the CAPRI blind test <url>http://www.ebi.ac.uk/msd-srv/capri</url>, more efforts need to be applied. Thus, the sampling protocol should generate a pool of conformations that include a sufficient number of near-native ones, while the scoring function should discriminate between near-native and non-near-native proposed conformations. On the other hand, protocols to efficiently include full flexibility on the protein structures are increasingly needed.</p> <p>Results</p> <p>In these work we present new computational tools for protein-protein docking. We describe here the RotBUS (Rotation-Based Uniform Sampling) method to generate uniformly distributed sets of rigid-body docking poses, with a new fast calculation of the optimal contacting distance between molecules. We have tested the method on a standard benchmark of unbound structures and we can find near-native solutions in 100% of the cases. After applying a new fast filtering scheme based on residue-based desolvation, in combination with FTDock plus pyDock scoring, near-native solutions are found with rank ≤ 50 in 39% of the cases. Knowledge-based experimental restraints can be easily included to reduce computational times during sampling and improve success rates, and the method can be extended in the future to include flexibility of the side-chains.</p> <p>Conclusions</p> <p>This new sampling algorithm has the advantage of its high speed achieved by fast computing of the intermolecular distance based on a coarse representation of the interacting surfaces. In addition, a fast desolvation scoring permits the screening of millions of conformations at low computational cost, without compromising accuracy. The protocol presented here can be used as a framework to include restraints, flexibility and ensemble docking approaches.</p